2026 The 13th International Conference on Artificial Intelligence (ICOAI 2026)
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About this event
Event Description: The 13th International Conference on Artificial Intelligence (ICOAI 2026)
The 13th International Conference on Artificial Intelligence (ICOAI 2026) will be held in Paris, France from September 25 to 27, 2026. As a prominent academic and industry gathering, ICOAI 2026 serves as a platform for researchers, engineers, educators, and professionals to exchange innovative ideas and advancements in the field of Artificial Intelligence (AI). The conference is part of the ICCSIT 2026 series and has a history of successful events in various European cities, including Spain, Italy, and The Netherlands.
Who Attends (Buyers / Attendees)
ICOAI 2026 attracts a diverse audience of:
- Academic researchers and professors from universities and research institutions.
- Industry professionals working in AI, machine learning, robotics, and related technologies.
- Engineers and developers from tech companies and startups.
- Educators and curriculum developers focused on AI and computer science.
- Government representatives and policymakers involved in technology regulation and innovation.
- Students pursuing advanced degrees in AI, computer science, and engineering.
- Executives and decision-makers from companies investing in AI applications across sectors like healthcare, automotive, manufacturing, and entertainment.
Location and Geographic Origin
Venue: The event will take place in Paris, France. While the exact venue name is not specified on the official website, previous ICCSIT events have been held in academic or conference centers.
Attendee Origin: The conference draws an international audience, with participants from academia and industry across Europe, North America, Asia, and other regions. Paris's status as a global hub enhances its appeal for global attendees.
Audience Reach
The audience reach of ICOAI 2026 is global. As an international conference, it attracts participants from various countries, reflecting the global nature of AI research and development. The event’s association with ICCSIT and its history of hosting international attendees further supports its global reach.
Sample Buyer Company Names and Websites
| Priority | Company | Website | Best Title to Target | Why This is a Good Buyer Fit |
|---|---|---|---|---|
| 1 | Google DeepMind | https://deepmind.com | AI Research Director | Leader in AI research and development, likely interested in academic collaborations and talent acquisition. |
| 2 | IBM Research | https://www.research.ibm.com | AI Innovation Manager | Active in AI advancements and often engages with academic conferences for partnerships and recruitment. |
| 3 | Intel AI | https://www.intel.com/content/www/us/en/artificial-intelligence.html | Director of AI Ecosystems | Invests in AI hardware and software solutions, seeking academic and industry collaborations. |
| 4 | Microsoft Research | https://www.microsoft.com/en-us/research | Principal Research Scientist (AI) | Engages in cutting-edge AI research and often collaborates with academic institutions. |
| 5 | NVIDIA AI | https://www.nvidia.com/en-us/deep-learning-ai/ | AI Technology Evangelist | Provides AI computing platforms and tools, interested in academic partnerships and developer ecosystems. |
| 6 | Thales Group - AI & Data | https://www.thalesgroup.com/en | Head of AI Research | European leader in AI for defense, aerospace, and security, seeking innovative research collaborations. |
| 7 | Orange Labs | https://www.orange-business.com/en/about-us/innovation/orange-labs/ | AI Research Program Manager | French telecom leader investing in AI for networks and services, active in academic partnerships. |
| 8 | Toyota Research Institute (TRI) | https://www.triGlobal.com | AI for Mobility Research Lead | Focuses on AI for autonomous vehicles and mobility solutions, interested in collaborative research. |
| 9 | SAP AI & Machine Learning | https://www.sap.com/technologies/ai-machine-learning.html | Director of AI Partnerships | Engages with academic institutions for AI innovations in enterprise software solutions. |
| 10 | Philips Research - AI & Data Science | https://www.philips.com/research | Chief Data Scientist (AI) | Applies AI in healthcare and consumer health, seeking research collaborations and talent. |
Job Profiles, Industries, and Event Type
Job Profiles:
- AI Researchers and Scientists
- Machine Learning Engineers
- Data Scientists
- AI Product Managers
- Academic Professors and Researchers
- Technology Development Managers
- AI Ecosystem Strategists
- AI Policy Advisors
Industries:
- Artificial Intelligence and Machine Learning
- Information Technology and Software Development
- Research and Development
- Education and Academia
- Healthcare Technology
- Automotive and Transportation (Autonomous Vehicles)
- Telecommunications
- Defense and Security
Event Type: Academic and Industry Conference focused on Artificial Intelligence research, development, and application.
Estimated Attendance
While the exact number of attendees for ICOAI 2026 is not provided on the official website, previous ICCSIT events have attracted several hundred participants, including researchers, industry professionals, and students. Given the growth of AI and the global reach of the conference, estimated attendance for ICOAI 2026 is around 500-800 participants, including presenters, exhibitors, and delegates.
Key Focus Areas and Buyer Engagement
Key Focus Areas:
- AI Algorithms and Applications
- Machine Learning and Deep Learning
- AI in Healthcare, Automotive, and Manufacturing
- AI Ethics and Policy
- AI Hardware and Infrastructure
- AI for Cybersecurity and Defense
Buyer Engagement Angle: The conference offers a unique opportunity to engage with buyers and decision-makers from both academia and industry. For companies, the focus should be on:
- Partnership Development with Academic Institutions
- Talent Acquisition and Recruitment of Researchers and Engineers
- Exhibition of AI Technologies and Platforms
- Collaborative Research Initiatives
- Brand Visibility among Global AI Stakeholders
Client Product Fit and Industry Recommendation
To provide a tailored buyer list, please share your client’s website and product details. Based on the event’s focus, industries that would find ICOAI 2026 particularly beneficial include:
- Artificial Intelligence and Machine Learning Companies
- Education Technology Providers
- Research Institutions and Universities
- AI Hardware and Infrastructure Providers
- Consulting Firms in AI and Technology
- Government Agencies Involved in Technology Policy
Final Recommendation
ICOAI 2026 is highly recommended for companies and institutions seeking to engage with the global AI community. The conference offers a strong platform for networking, collaboration, and showcasing innovations. For attendee list sales, focus on academic and industry decision-makers, researchers, and technology leaders. The event’s global reach and technical focus make it an excellent opportunity for targeted outreach.
Data sheet
2026 The 13th International Conference on Artificial Intelligence (ICOAI 2026) – Event Attendee & Buyer Profile Analysis
Event date: September 25–27, 2026
Location: Paris, France
Event status: Upcoming
Research date: June 29, 2026
Event Overview
| Event Name | The 13th International Conference on Artificial Intelligence (ICOAI 2026) |
| Event Date | September 25–27, 2026 |
| Event Status | Upcoming |
| Venue | Venue not publicly specified in the provided official homepage text |
| City | Paris |
| State / Region | Île-de-France |
| Country | France |
| Organizer | Official organizer name not clearly stated in the provided homepage text; conference administration contact is listed via iacsit.net email domain and ICOAI is stated to be a workshop of ICCSIT 2026 |
| Official Event Website | www.icoai.org |
| Event Type | International conference / academic and industry workshop |
| Primary Category | IT & Technology |
| Secondary Applicable Categories | Science & Research; Education & Training |
| Audience Reach | Global |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Low for numeric attendance; high for dates, city, country, and conference positioning based on official website text |
| Main Purpose of Event | Research exchange, paper presentation, academic-industry networking, AI innovation discussion, publication, and professional learning across artificial intelligence applications and platforms |
About the Event
ICOAI 2026 is an international artificial intelligence conference scheduled for September 25–27, 2026 in Paris, France. According to the official event website, the conference is positioned as a forum where academia and industry meet to exchange experiences, present studies, and advance AI technologies across areas such as manufacturing, automotive, healthcare, robotics, entertainment, cloud systems, edge devices, and computing platforms.
From a business development standpoint, ICOAI 2026 is more valuable for expert-led B2B outreach, partnership sourcing, research collaboration, AI infrastructure conversations, software/tool adoption, and academic-enterprise relationship building than for mass-market exhibition footfall. The attendee mix is likely to include researchers, professors, engineers, developers, graduate students, industry practitioners, and selected decision-makers from organizations investing in AI systems, applied machine learning, and computing environments.
1. Who Attends: Buyers / Attendees
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| University researchers and professors | Universities, engineering schools, AI labs, public research institutes | Influence software selection, datasets, compute platforms, lab tools, and research partnerships | High relevance for AI platforms, cloud credits, developer tools, model evaluation tools, and collaborative research programs |
| Industry AI engineers and developers | Software firms, AI startups, enterprise innovation teams, robotics firms | Technical evaluators and implementation influencers | Useful for product-led outreach, pilot programs, API adoption, and engineering-level demos |
| R&D leaders and innovation managers | Advanced manufacturing, automotive, healthcare technology, semiconductor, and systems companies | Budget influence for experimentation, proof-of-concept projects, and external collaborations | Good targets for applied AI solutions, simulation, data infrastructure, model deployment, and embedded AI offerings |
| Educators and curriculum developers | Higher education institutions, continuing education providers, computer science departments | Influence learning platform adoption and training partnerships | Relevant for academic content providers, edtech, certification, and lab software vendors |
| Technology executives and digital transformation leaders | Enterprise AI adopters across healthcare, automotive, manufacturing, media, and services | Strategic buyers for AI deployment, governance, and vendor evaluation | Important for higher-value sales around AI operations, governance, infrastructure, and enterprise applications |
| Government representatives and policy stakeholders | Technology ministries, innovation agencies, research funding bodies, regulators | Influence policy, funding, public research collaboration, and standards adoption | Relevant for public-sector AI solutions, compliance, grants, and research consortia |
| Graduate students and doctoral candidates | Universities and research programs | Low direct budget authority, high future influence and technical adoption potential | Useful for talent pipeline building, developer community growth, and future-user acquisition |
| Conference delegates without paper submission | Independent professionals, corporate attendees, consultants, technical practitioners | Mixed; often exploratory, networking, and market-scanning roles | Good for targeted follow-up, thought leadership content, and niche B2B outreach |
2. Event Location and Attendee Geographic Origin
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Paris | Local academics, laboratories, AI practitioners, engineering schools, and innovation teams | High | Paris is a major European research, startup, and enterprise technology hub |
| Île-de-France | Regional universities, corporate R&D centers, and public innovation stakeholders | High | Likely source of nearby delegates and day attendees |
| France | National researchers, applied AI companies, engineering universities, public research bodies | High | Strong domestic participation is likely, especially from research and technology networks |
| Western and Central Europe | Researchers and corporate AI teams from nearby European countries | Medium to High | Historical conference rotation across European cities supports European reach |
| International | Academia and industry delegates from broader global AI community | Medium | The event is explicitly positioned as an international conference and welcomes delegates beyond paper presenters |
| Application-sector trade corridors | Manufacturing, automotive, healthcare, robotics, entertainment, cloud, and edge-computing ecosystems | Medium | These verticals are specifically referenced in the official event description |
3. Audience Reach
| Reach Level | Assessment | Explanation |
|---|---|---|
| Global | Primary classification | The conference is explicitly branded as international, invites delegates globally, and connects academia with industry across multiple AI application domains. |
| European | Secondary practical reach | Paris location and prior editions in European cities suggest a strong European attendee core. |
| National | Secondary practical reach | French research institutions, universities, and AI innovation stakeholders are likely to be well represented. |
4. Sample Buyer Companies and Websites
Current-year attendee and exhibitor lists were not publicly identified in the provided official source text. The table below is limited to organizations explicitly named in official ICOAI 2026 materials or directly tied to the conference ecosystem. It should not be treated as a full confirmed attendee list.
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| University of Haute-Alsace | Academic sponsor | Officially named as sponsor of ICOAI 2026; relevant for research collaboration, AI education, and computing tools | uha.fr | Professor, Research Director, Dean, Head of Lab, IT Director | Confirmed Sponsor / Exhibitor |
| Conservatoire National des Arts et Métiers | Higher education and research institution | Official keynote speaker organization confirmed in conference news | cnam.fr | Professor, Research Chair, AI Program Director, Lab Director | Confirmed Speaker Organization |
| ACM | Professional computing association / publication ecosystem stakeholder | Accepted papers may be published in ACM conference proceedings as a chapter of ICCSIT 2026 | acm.org | Publications Manager, Conference Program Lead, Partnerships Director | Confirmed Current-Year Participant |
| Journal of Advances in Information Technology | Academic journal | Listed by the conference as a publication outlet for accepted papers based on topic | jait.us | Editor, Publications Director, Journal Manager | Confirmed Current-Year Participant |
| International Journal of Machine Learning | Academic journal | Listed by the conference as a publication outlet for accepted papers based on topic | ijml.org | Editor, Journal Administrator, Publications Manager | Confirmed Current-Year Participant |
| ACM Digital Library | Research publishing platform | Officially named as the archive venue for conference proceedings series | dl.acm.org | Digital Library Manager, Publications Lead, Content Partnerships | Confirmed Current-Year Participant |
| Ei Compendex | Indexing ecosystem stakeholder | Named in official publication information as an indexing target for proceedings | engineeringvillage.com | Indexing Program Manager, Academic Partnerships | Confirmed Current-Year Participant |
| Scopus | Research indexing ecosystem stakeholder | Named in official publication information as an indexing destination | scopus.com | Content Partnerships, Indexing Relations, Research Solutions Manager | Confirmed Current-Year Participant |
| EBSCO | Research database ecosystem stakeholder | Officially listed in journal abstracting and indexing references | ebsco.com | Academic Solutions Manager, Database Partnerships | Confirmed Current-Year Participant |
| Google Scholar | Academic discovery ecosystem stakeholder | Named in official journal indexing references; relevant to publication visibility and research dissemination | scholar.google.com | Research Partnerships, Academic Program Manager | Confirmed Current-Year Participant |
| CNKI | Research indexing and academic database stakeholder | Named in official publication indexing references | cnki.net | Content Acquisition Manager, Academic Relations | Confirmed Current-Year Participant |
| IET Inspec | Indexing ecosystem stakeholder | Named in official journal indexing references for IJML | theiet.org | Indexing Relations, Academic Partnerships | Confirmed Current-Year Participant |
5. Job Profiles, Industries and Event Type
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | Professor / Principal Investigator | Research / Academic | Senior | Core decision-makers for lab tools, collaborations, datasets, and publication partnerships |
| 2 | Director of AI / Head of AI | AI / R&D | Director | High-value buyer for enterprise AI solutions, applied research, and deployment platforms |
| 3 | Research Director | Research & Development | Director | Owns research agenda, grants, external collaborations, and technical evaluation |
| 4 | Machine Learning Engineer | Engineering | Manager / Individual Contributor | Key technical evaluator for APIs, infrastructure, frameworks, and developer tools |
| 5 | CTO | Executive / Technology | C-Level | Strategic buyer for AI adoption, architecture, and platform investments |
| 6 | IT Director | Information Technology | Director | Relevant for infrastructure, data management, security, and platform integration decisions |
| 7 | Innovation Manager | Innovation / Strategy | Manager | Scouts external AI partners, pilots, and new technologies |
| 8 | Program Manager, AI Research or Innovation | Programs / Research | Manager | Coordinates grants, projects, partnerships, and technology pilots |
| 9 | Dean / Head of Department | Academic Administration | Senior | Important for education technology, strategic collaboration, and curriculum initiatives |
| 10 | Partnerships Director | Business Development / Partnerships | Director | Relevant for sponsorships, collaborative research, ecosystem alliances, and institutional deals |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Information Technology & Services | Direct match for enterprise AI, software integration, cloud, and applied AI services | AI software, implementation, data and model operations |
| 2 | Computer Software | Strong fit for AI product companies, frameworks, tooling, and enterprise applications | Developer tools, AI platforms, analytics, automation |
| 3 | Research | Core fit for academic and non-academic research institutions participating in AI advancement | Lab software, collaboration tools, data services |
| 4 | Higher Education | Universities and engineering schools are likely core participants | Curriculum, labs, academic partnerships, compute access |
| 5 | Industrial Automation | Official description references manufacturing and applied AI systems | AI for process optimization, predictive systems, robotics |
| 6 | Automotive | Automotive is explicitly named as an AI application area | Computer vision, autonomy, simulation, embedded AI |
| 7 | Hospital & Health Care | Healthcare is specifically mentioned by the conference | Clinical AI, imaging, decision support, analytics |
| 8 | Medical Devices | Relevant for AI-enabled instrumentation and diagnostic applications | Embedded inference, edge devices, validation tooling |
| 9 | Electrical/Electronic Manufacturing | Official text references circuit-level and system-level computing support for AI | Edge hardware, accelerators, inference devices |
| 10 | Computer Hardware | Relevant for AI compute platforms from cloud to edge | Servers, accelerators, embedded compute, evaluation kits |
| 11 | Government Administration | Government representatives and policy stakeholders are part of the likely audience profile | Public-sector AI initiatives, compliance, innovation programs |
| 12 | Education Management | Relevant for academic administration, AI curriculum, and institutional technology adoption | Training platforms, certification, teaching labs |
6. Estimated Attendance
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Attendance figure not publicly confirmed by the organizer. | Not confirmed | No attendee count published in provided official text | Use direct organizer outreach if a numeric estimate is required for list-building decisions |
| Exhibitor count | Not publicly confirmed | Not confirmed | No exhibitor directory identified in provided source | Academic conference format suggests limited traditional expo activity |
| Buyer count | Not publicly confirmed | Not confirmed | No buyer program published in provided source | This event is more conference-led than procurement-led |
| Speaker count | At least 1 keynote organization named in provided text | Partially confirmed | Official news update confirms Prof. Conan Vania of CNAM | Full speaker lineup not available in the provided text extract |
| Sponsor count | At least 1 sponsor named | Partially confirmed | Official news update names University of Haute-Alsace | Other sponsor categories are shown but names are not visible in the provided text |
| Historical attendance | Not publicly confirmed in provided source | Historical / prior-year evidence unavailable | History pages are listed in navigation but attendance figures were not provided in the supplied text | No reliable numeric historical benchmark included here |
7. Key Focus Areas and Buyer Engagement
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Artificial Intelligence research | Methods, publications, benchmarking, peer exchange | Research collaboration outreach, publication support, tool trials | Model development platforms, datasets, experiment tracking, MLOps |
| Cloud and edge computing for AI | Scalable training and deployment environments | Technical demos, infrastructure comparisons, pilot offers | Cloud compute, edge hardware, accelerators, orchestration tools |
| Manufacturing AI | Predictive optimization, automation, quality intelligence | Applied use-case workshops and proof-of-concept engagement | Industrial analytics, vision systems, IoT-to-AI integrations |
| Automotive AI | Vision, autonomy, simulation, embedded intelligence | Engineering-led discussions and technical validation | Simulation software, sensor processing, real-time inference |
| Healthcare AI | Clinical decision support, imaging, prediction, workflow intelligence | Pilot partnerships, validation studies, hospital innovation discussions | Medical AI software, analytics, secure data environments |
| Robotics and intelligent systems | Perception, control, autonomy, hardware-software integration | Lab collaboration and systems prototyping outreach | Robotics software, simulation, embedded hardware, control systems |
| Education and training | AI curriculum, teaching tools, student enablement | Academic licensing and curriculum partnership offers | Edtech, labs, courseware, certification platforms |
| Research publication and dissemination | Visibility, indexing, peer-reviewed dissemination | Publishing ecosystem outreach and academic partnership building | Publishing support, editorial systems, indexing services |
Lead Quality Assessment
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | Medium to High | Strong for AI tools, infrastructure, research services, academic partnerships, and enterprise innovation offerings; weaker for broad consumer or non-technical products |
| Decision-maker availability | Medium | Academic leaders and technical evaluators are likely present, but formal procurement teams may be limited |
| Data collection potential | Medium | Useful for targeted relationship mapping and speaker/sponsor intelligence; less suitable for large-scale attendee list harvesting without official directory access |
| Apollo targeting potential | High | The event maps cleanly to AI, software, research, higher education, healthcare, hardware, and automation buyer profiles |
| Geographic targeting potential | High | Clear concentration in Paris, France, broader Europe, and international AI research networks |
| Best outreach approach | High | Use expert-led outreach, technical value propositions, co-research angles, and product trial offers rather than generic sales messaging |
| Overall lead quality | High for niche AI B2B; Medium for broad lead volume | Best suited for specialized targeting and relationship-based selling |
| Best use case | High | Account-based outreach, AI research partnerships, academic-enterprise introductions, technical product prospecting |
| Limitations / risks | Medium | No publicly confirmed attendance figures, no visible attendee directory in the provided source, and conference format may yield fewer classic procurement contacts than trade expos |
Apollo.io Targeting Recommendation
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Information Technology & Services; Computer Software; Research; Higher Education; Industrial Automation; Automotive; Hospital & Health Care; Medical Devices; Electrical/Electronic Manufacturing; Computer Hardware; Government Administration; Education Management | Build a high-fit AI event prospect universe |
| Departments | Engineering; Information Technology; Research; Education; Operations; Business Development; Partnerships | Focus on technical evaluators and institutional decision-makers |
| Seniority | C-Level; VP; Director; Head; Manager; Senior; Professor-equivalent where available | Prioritize budget holders and technical champions |
| Job titles | CTO; Director of AI; Head of AI; Research Director; Professor; Principal Investigator; Machine Learning Engineer; AI Engineer; IT Director; Innovation Manager; Dean; Head of Department; Partnerships Director; Program Manager | Mirror the likely ICOAI audience profile |
| Geography | France; Île-de-France; Paris; Germany; Netherlands; Italy; Spain; Belgium; Switzerland; United Kingdom; broader Europe if volume is needed | Align with host market and likely European conference draw |
| Employee size | 11–50; 51–200; 201–500; 501–1,000; 1,001–5,000; 5,001+ | Capture startups, research spinoffs, universities, and enterprise adopters |
| Keywords | artificial intelligence, machine learning, deep learning, computer vision, NLP, robotics, edge AI, MLOps, cloud AI, research lab, AI platform, intelligent systems | Surface organizations aligned to event themes |
| Technologies | If available: Python, TensorFlow, PyTorch, AWS, Azure, GCP, Kubernetes, NVIDIA, computer vision stack | Refine toward active AI builders and deployers |
| Revenue range | Optional; use open if prospecting universities and public research institutions, or mid-market to enterprise for commercial AI buyers | Separate academic accounts from enterprise software buyers |
| Company type | Private; Public; Educational Institution; Nonprofit; Government where relevant | Broaden capture across academic, public, and commercial AI ecosystems |
Suggested Apollo Search Logic: ("artificial intelligence" OR "machine learning" OR "deep learning" OR "computer vision" OR robotics OR "edge AI" OR MLOps) AND (France OR Paris OR Europe) AND (CTO OR "Head of AI" OR "Research Director" OR Professor OR "Machine Learning Engineer" OR "Innovation Manager").
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Sources & Verification Notes
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| ICOAI 2026 Official Website | Official event website | Official event name, date, city, country, conference scope, delegate registration availability, publication details, important deadlines, sponsor mention, keynote organization, and historical positioning | High |
| Provided official homepage text extract | Primary source content supplied by user | Confirmed that the official website states September 25–27, 2026 in Paris, France; this supersedes conflicting user-supplied draft dates | High |
| Official news items on the ICOAI 2026 website | Official event updates | Verified sponsor reference to University of Haute-Alsace and keynote confirmation for Conservatoire National des Arts et Métiers | High |
Suitability for B2B attendee list building: Moderate. ICOAI 2026 is highly relevant for specialized AI, research, academic, and innovation-focused outreach, but the provided official source does not publish a current attendee directory or attendance figures.
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Tell us your work email and our AI instantly builds a buyer list matched to 2026 The 13th International Conference on Artificial Intelligence (ICOAI 2026) — the best‑fit companies to target, the exact decision‑maker job titles, and the industry filters that fit what you sell.
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